Agentic Invoice Parser –

This repository contains the capstone project for the Post Graduate Program in AI & Machine Learning – an Agentic Workflow-based Invoice Parser designed to extract structured data from complex Indian invoice PDFs.

Project Overview

In real-world enterprise settings, invoices often arrive as PDF files containing multiple invoices, with each invoice potentially spanning multiple pages and including tables, images, and varied layouts. This project leverages an agentic architecture to intelligently parse, segment, and extract relevant information from such documents into a structured schema.

Built using Pydantic-AI and Pydantic-Graph, the workflow uses Large Language Models (LLMs) to reason through document structure and extract key fields in a reliable, modular fashion.

Here is The workflow

Features

Very Minimum Cost Per page: < 50 paisa /per page
Multi-invoice PDF support: Automatically detects and segments individual invoices from a single PDF.
Multi-page invoice parsing: Handles invoices that span across several pages.
Agentic workflow: Implements modular agent steps using Pydantic-AI and Pydantic-Graph.
Structured output: Extracted data is validated and output using a well-defined Pydantic schema.
Table & key-value extraction: Supports varied layouts including tables, text blocks, and image-embedded sections.

Working on Observability

Tech Stack

Python
Pydantic / Pydantic-AI
Pydantic-Graph
LLMs (llama 4/ openai)
pypdfium2 - (PDF to Images)
Pydantic-settings - (Config Management)
Project Management uv

How to Run

Install Dependencies

   uv sync --frozen --no-dev

Run the Parser

    uv run main.py path/to/the/invoice.pdf

The Invoice JSON Schema

RahulDas-dev/invoice-parser

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